News

Representatives of the coordinating teams of SAFEXPLAIN and ULTIMATE met to share progress, lessons learnt, and look for potential opportunities for synergies. They delved deeper into the issues that concern both projects: TrustworthyAI.

The space scenario envisions a crewed spacecraft performing a docking manoeuvre to an uncooperative target (a space station or another spacecraft) on a specific docking site. The GNC system must be able to acquire the pose estimation of the docking target and of the spacecraft itself, to compute a trajectory towards the target and to send commands to the actuators to perform the docking manoeuvre. The safety goal is to dock with adequate precision and avoid crashing or damaging the assets.

SAFEXPLAIN consortium meets halfway through the project at RISE venue in Lund With the first 18 months of the project behind it, the SAFEXPLAIN consortium met in Lund from 16-17 April to discuss project status and next steps for the next 18 months. Great strides have...

AI-generated image of object detection for automotive Artificial intelligence, and more specifically, Deep Learning algorithms are used for visual perception classification tasks, like camera-based object detection. For these tasks to work, they need to identify the...

Jon Perez Cerrolaza presenting the CARS WS keynote The SAFEXPLAIN project opened the 8th edition of the Critical Automotive applications: Robustness & Safety (CARS) workshop on 8 April 2024, with a keynote talk, delivered by Ikerlan partner Jon Perez-Cerrolaza on...

Figure 1: Project coordinator, Jaume Abella, at the BSC booth at MWC24 The 2024 Mobile World Congress in Barcelona offered the SAFEXPLAIN project the opportunity to meet key industry players from the global mobile ecosystem. Moreover, it granted the project partner...

Exida is part of two technical pillars that are associated with two major work-packages (WP) of the project: WP2- Safety Assessment and WP4 -Platforms and Toolset Support. The intermediate results of which are presented in this text.

We´re celebraiting the 9th Anniversary of #FEBRUARY11 Global Movement with a look into the women in science and technology in the project.

The SAFEXPLAIN projects counts with the participation of many women in science who are driving the project´s success. See what advice they have for young scientists.

SAFEXPLAIN is developing an AI-Functional Safety Management methodology that guides the development process, maps the traditional lifecycle of safety-critical systems with the AI lifecycle, and addreses their interactions. AI-FSM extends widely adopted FSM methodologies that stem from functional safety standards to the the specific needs of Deep Learning architecture specifications, data, learning, and inference management, as well as appropriate testing steps. The SAFEXPLAIN-developed AI-FSM considers recommendations from IEC 61508 [5], EASA [6], ISO/IEC 5460 [3], AMLAS [7] and ASPICE 4.0 [8], among others.

SAFEXPLAIN partners from IKERLAN and the Barcelona Supercomputing Center met with TÜV Rheinland experts on 22 January 2024 to share the project´s AI-Functional Safety Management (AI-FSM) methodology. This meeting provided an important opportunity for the project to present its work to an important player in safety certification.